PrimeEditing
Prime Editing Prediction & Efficiency Factors
Understand and model what drives pegRNA efficiency.
Explore pegRNA efficiency drivers—RTT/PBS length, nick offsets, sequence context—with evidence passes inside Helix Studio, the Genome IDE.
System of Record →Section 1
What the tool is
The model implied evidence view explains which factors most influence your pegRNA performance and lets you test alternatives quickly.
Section 2
Why scientists care
Prime Editing can feel opaque; teams iterate blindly without knowing which parameter to change.
Section 3
How Helix solves it
Factor ranking showing contribution of RTT/PBS length, GC, and nicking geometry
Section 4
How the algorithm works
Models combine published PE datasets with Helix heuristics for priming stability and nick synchronization.
Section 5
Try it in Helix Studio
Load your pegRNA, tweak RTT/PBS lengths or nick positions, and watch efficiency estimates update.
Section 6
FAQ
What datasets back the model implied evidence?
Published Prime Editing benchmarks plus Helix-internal heuristics for stability and geometry.
Can I override the model?
Set manual weights or pin certain parameters; Helix will still track changes and model implied evidence.
Do you handle multi-edit scenarios?
Yes—efficiency previews can be run per edit or across a multiplexed set with shared context.